The proposed research applies an innovative network measurement application - Cell-phone Assisted Network Detection and Identification (CANDID) - to establish a communication network and examine its relation to health related behaviors for men at high risk for HIV infection. Most network studies of health and behavior have used egocentric surveys of individuals that depend on respondents generating the names of alters in their network and providing information on them. However, the utility of egocentric data collection for network characterization has several clear limitations. Recent advances in use of archival computerized network data including email messages, citations, and cell phone provider data has allowed for more objective analyses of whole network structure. However, deficiencies in health or behavioral information are inherent to such datasets. We plan to address at least two limitations of current basic network research: respondent bias (recall, recognition and forgetting) and deficiencies in archival network data (especially the lack of behavioral health related data) by applying a newly developed network measurement algorithm, CANDID, combined with a name interpreter. CANDID is a low-cost application that utilizes a cell-phone Subscriber Identity Module (SIM) card reader and associated software to allow for tie/alter identification from respondents' cell phone contact lists. A transformation of cell phone numbers will serve as a unique identifier for each respondent and contact. With strong privacy protections in place, we are able to unambiguously link contact lists of all sampled respondents to generate an augmented network, that is, network tie information for respondents plus tie information for all other actors (including non-sampled actors). Name interpreter data of sampled respondents then provides complementary tie/alter attribute information. This approach of linking cell phone contact lists from sampled respondents combines archival and egocentric network data collection allowing for measurement of undirected and directed ties between actors with confidence and through survey data, tie attributes and actor health behavior characteristics. This hybrid approach will be leveraged to explore communication network structures in Indian men who have sex with men (MSM). It will then be specifically applied via an empirical analytic framework to explore the complex interactions between marital status, sex position and HIV risk among a large augmented network of Indian MSM.